Given the revision to the Act on Temporary Measures for Promotion of Rational Uses of Energy and Recycled Resources in Business Activities enacted in April 2010, that which is subject to regulation has changed from business location units, such as factories and buildings, to business (company) units that include a plurality of business locations. As a result, if the total amount of energy used annually throughout in a company, such as in its headquarters, its factories, its branches, its business locations, and the like, exceeds a crude-oil equivalent of 1500 kL, then that company will be under obligation to file reports. Companies that are subject to the Act on Temporary Measures for Promotion of Rational Uses of Energy and Recycled Resources in Business Activities typically are subject to obligations for reporting under the Law Concerning the Promotion of the Measures to Cope with Global Warming as well. These companies must establish long-term plans for reducing energy consumption, record and archive amounts of energy used monthly, tabulate results, and file periodic reports. It is necessary for these companies to be able to know the amounts of energy used at a plurality of geographically separated locations in order to control the total amount of energy used. Moreover, if a firm is unable to achieve reduction targets, then it may be subject to civil penalties under local regulations, and may experience a loss in corporate value from the perspective of corporate social responsibility (CSR).
Conventionally, typically the system for controlling the total amount of energy used has been a total energy use controlling system wherein individuals at each individual business location would input, from an inputting screen of a web-based system, monthly data for the amount of energy used (electricity, gas, etc.), where these data would be collected and controlled in a database on a server, to provide trends in the amount of energy used at individual locations or in all locations together (See, for example, Takahashi, Tatsunori, et al.: “‘Net Enercare-e’—An Energy Controlling Service Supporting the Revised Energy Conservation Act,” Hitachi Hyoron, Vol. 92, No. 03, p. 26-29, March 2010).
FIG. 16 shows an overview of a typical web-based energy use controlling system. The energy use controlling system is structured from: terminal devices 101-A through 101-C provided at individual controlled locations A through C, such as the headquarters, factories, branches, business locations, retail locations, and the like; a server 102 that is provided at, for example, a control center; and the Internet 103, which is a network for connecting the terminal devices 101-A through 101-C and the server 102. As illustrated in FIG. 16, when data for the amount of energy used by each of the controlled locations are inputted into the terminal devices 101-A through 101-C, based primarily on workers at the individual controlled locations A-C looking at the meters, and on invoices, the data for the amount of energy used are stored in a database 104 of the server 102 through the Internet 103.
While there are also cases wherein data on the amount of energy used is collected automatically through measurement equipment such as electric meters in each of the controlled locations A through C, regardless of whether the data is collected manually or automatically, the data for all of the controlled locations are stored in a server 102 so as to make it possible for the individual in the firm with responsibility for environmental control (hereinafter termed the “total quantity administrator”) to review the compiled results. A comparison of the monthly or yearly energy use reduction target values (hereinafter termed “target values”) to the actual results for the amounts of energy use can be viewed in graphic displays, or the like, in a controlling screen for the total quantity administrator, displayed by the server 102.
The total quantity administrator controls each of the locations through, for example, comparing the total calculated value for the amounts of energy used in each of the controlled locations to the target values for the amount of energy used that month, and directing energy reductions in the various controlled locations if it is determined that the target values for the amount of energy used throughout the year will be exceeded, to control each location so that the amounts of energy used throughout the year will be no more than the target values. While the data on the amounts of energy used are collected through employees at each of the controlled locations inputting the data or through measurements by measuring devices, as described above, an energy controlling system has also been proposed wherein energy-related information that is not measured is inferred through analysis of other measurement information (See, for example, Japanese Unexamined Patent Application Publication 2004-280618).
In a location of a small scale, or a location wherein a tenant resides, or the like, there are cases wherein implementation of measurement devices or systems for collecting management data automatically into the server is not possible due to high implementation costs, and cases wherein the provision of a system would be difficult due to problems in compatibility with existing equipment, and thus there are many cases wherein the employees at the individual controlled locations input manually the amounts of energy used each month, based on meter readout reports or invoices. However, the timing with which the distribution of meter readout reports or invoices, or the like, for electricity, gas, and the like, are different for each business location, and, in particular, in a location wherein there is tenant occupancy, the invoices from the tenant owners will not necessarily be issued the following month, but there are also cases wherein, for example, they are not issued until three months have elapsed.
The data that is checked will be described hereafter. In a conventional systems, it is not possible to collect the total amount of energy used (hereinafter termed “the total energy quantity”) in a given month until all of the amounts of energy used in all of the controlled locations have been confirmed by the total quantity administrators, and thus there is a problem in that the evaluation as to whether or not there is a likelihood that the yearly target value will be exceeded by the total energy quantity will be delayed. When this leads to a delay in researching and implementing countermeasures, there will be a high likelihood that it will not be possible to keep the total amounts of energy used in a year to with in the target values.
The conventional problem area will be described in greater detail below. FIG. 17 illustrates an abstracted image of the energy usage quantity data for fiscal 2009, collected for an arbitrary location X. In the example in FIG. 17, the data regarding the amount of energy used are shown with squares rather than specific numbers. As is clear from this example, the usage quantity data for each month is stored in the server for the controlled energy types, for the controlled locations.
FIG. 18(A) is a diagram illustrating an example of the amount of energy used for each controlled location, where FIG. 18(B) is a diagram illustrating an example of the total energy quantity wherein the energy use quantities of the individual controlled locations have been summed together. In FIG. 18(B), the total energy quantity for each month is calculated by summing, for each month, the amounts of energy used by each of the controlled locations, and it can be seen that the total energy quantities for the individual months are summed to calculate a yearly total cumulative energy quantity Etotal for the year. There is a need to control energy usage so that this total cumulative energy quantity Etotal will not exceed the yearly energy use quantity target values.
FIG. 19 is a diagram illustrating an example wherein undetermined data is included in the data on the amount of energy used in fiscal 2009 at a location X. For simplicity in the explanation, the controlled energy types will be limited to only electricity, gas, and oil. In the example in FIG. 19, the white squares indicate confirmed data and the black squares indicate non-confirmed data. In this example, the data for September 2009 onward is non-confirmed, and in the data for August 2009, only electricity is confirmed, where, in the data for July 2009, only oil is confirmed, where all of the data is confirmed in June 2009 and earlier. In this case, the data subject to calculation in total quantity control in the prior art would be only those months wherein all of the data has been confirmed. That is, in the example in FIG. 19, it would be from April 2009 until the last month wherein there is data that is completely confirmed (hereinafter termed the “last confirmed month”), which is data up to June 2009.
FIG. 20(A) is a diagram illustrating an example wherein non-confirmed data is included in the energy usage quantity in each controlled location, and FIG. 20(B) is a diagram illustrating a case of a total energy quantity wherein the energy use quantities of each of the controlled locations have been summed. For simplicity in the explanation, let us assume only two controlled locations A and B, with only electricity, gas, and oil as the controlled energy types. In the example in FIG. 20(A), the white squares indicate confirmed data and the black squares indicate non-confirmed data.
If, as in the example in FIG. 20(A), the last confirmed month in the controlled location A is August and the last confirmed month for controlled location B is June 2009, then, in the conventional system, the last month for which the total quantity is calculated by compiling the total quantity control data would be June 2009, where the monthly data for both of the controlled locations A and B are confirmed. Regardless of the data for July 2009 and the data for August 2009 in controlled location A being confirmed, these confirmed data are not used. As described above, there is a variety of variation in the timing with which data is confirmed, depending on the controlled location, the type of energy, and the like, and, in particular, for a location wherein a tenant resides, invoices are not necessarily issued from a tenant owner the following month, but, for example, there are also cases wherein they are not issued until after three months.
The total quantity administrator needs to be able to discover as quickly as possible situations wherein total energy quantity targets may not be achieved (wherein the actual value for the total energy quantity will exceed the reduction target value), to establish the required countermeasures as quickly as possible. However, in the conventional system, it is not possible to compile the total energy quantities for a given month until all of the energy usage quantities for all of the controlled locations are confirmed, and thus there may be delays in evaluating whether or not the yearly conservation target values will be exceeded, due to delays in understanding the total energy quantities for a given month. In the conventional system, in the case of the data illustrated in FIG. 20, often the actual values for the total energy quantities for each month of the prior fiscal year are displayed as reference values for July 2009 and forward, in the case of the data illustrated in FIG. 20. However, even if, for example, there were one location wherein the amount of energy usage was small, if even only that is not confirmed, the calculation process would not be performed regardless of the total energy quantity for the month being essentially established.
The present invention is to solve the problem set forth above, and the object thereof is to provide a total energy quantity controlling device and method able to reduce the probability that a total energy quantity target will not be met, through using substitute data to calculate the total amount of energy used if there is unconfirmed data in the amount of energy used.